A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy
Objective: The objective of this study was to evaluate the characteristics of high body mass index (BMI) and normal weight people living with HIV after antiretroviral therapy (ART) and establish a model. Methods: A total of 290 people living with HIV after 1 year of ART treatment were enrolled and d...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
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SAGE Publishing
2022-06-01
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Series: | Therapeutic Advances in Chronic Disease |
Online Access: | https://doi.org/10.1177/20406223221102750 |
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author | Zhe Qian Houji Wu Yihua Wu Wei Liao Tao Yu Xuwen Xu Jie Peng Shaohang Cai |
author_facet | Zhe Qian Houji Wu Yihua Wu Wei Liao Tao Yu Xuwen Xu Jie Peng Shaohang Cai |
author_sort | Zhe Qian |
collection | DOAJ |
description | Objective: The objective of this study was to evaluate the characteristics of high body mass index (BMI) and normal weight people living with HIV after antiretroviral therapy (ART) and establish a model. Methods: A total of 290 people living with HIV after 1 year of ART treatment were enrolled and divided into two groups based on whether their BMI index was <24 or ⩾24 at week 48. The demographic, clinical data were collected and analyzed. Multivariable logistic regression analysis was performed. A model was established and use to predict the occurrence of certain diseases. Results: A total of 290 people living with HIV were included in this study; 200 had a normal BMI (BMI < 24) and 90 were high BMI (BMI ⩾ 24) after 1-year ART. Their baseline characteristics were significantly different in relation to age ( p = 0.007), sex distribution ( p = 0.040), ART regimen ( p = 0.040), alanine aminotransferase levels ( p < 0.001), and three major serum lipid levels: triglycerides ( p < 0.001), cholesterol ( p = 0.011), and low-density lipoprotein ( p = 0.005). A multivariate logistic regression analysis resulted in the development of a model for the diagnosis of high BMI and hyperlipidemia. The model score is an independent risk factor for hyperlipidemia (odds ratio = 2.674, p = 0.001) and high BMI ( p < 0.001). The model score is significantly correlated with the controlled attenuation parameter (CAP) value ( r = 0.230, p < 0.001) and can be used to divide the severity of liver steatosis based on CAP value. Conclusions: This study demonstrated a easy-to-use model to detect high BMI, hyperlipidemia, and liver steatosis in people living with HIV without risk factors for BMI changing at baseline after 1 year of ART treatment. |
first_indexed | 2024-04-13T16:56:15Z |
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id | doaj.art-ca447de3c3e8452586cbd1bb2eb2c5ac |
institution | Directory Open Access Journal |
issn | 2040-6231 |
language | English |
last_indexed | 2024-04-13T16:56:15Z |
publishDate | 2022-06-01 |
publisher | SAGE Publishing |
record_format | Article |
series | Therapeutic Advances in Chronic Disease |
spelling | doaj.art-ca447de3c3e8452586cbd1bb2eb2c5ac2022-12-22T02:38:48ZengSAGE PublishingTherapeutic Advances in Chronic Disease2040-62312022-06-011310.1177/20406223221102750A model for predicting high BMI of people living with HIV after receiving antiretroviral therapyZhe QianHouji WuYihua WuWei LiaoTao YuXuwen XuJie PengShaohang CaiObjective: The objective of this study was to evaluate the characteristics of high body mass index (BMI) and normal weight people living with HIV after antiretroviral therapy (ART) and establish a model. Methods: A total of 290 people living with HIV after 1 year of ART treatment were enrolled and divided into two groups based on whether their BMI index was <24 or ⩾24 at week 48. The demographic, clinical data were collected and analyzed. Multivariable logistic regression analysis was performed. A model was established and use to predict the occurrence of certain diseases. Results: A total of 290 people living with HIV were included in this study; 200 had a normal BMI (BMI < 24) and 90 were high BMI (BMI ⩾ 24) after 1-year ART. Their baseline characteristics were significantly different in relation to age ( p = 0.007), sex distribution ( p = 0.040), ART regimen ( p = 0.040), alanine aminotransferase levels ( p < 0.001), and three major serum lipid levels: triglycerides ( p < 0.001), cholesterol ( p = 0.011), and low-density lipoprotein ( p = 0.005). A multivariate logistic regression analysis resulted in the development of a model for the diagnosis of high BMI and hyperlipidemia. The model score is an independent risk factor for hyperlipidemia (odds ratio = 2.674, p = 0.001) and high BMI ( p < 0.001). The model score is significantly correlated with the controlled attenuation parameter (CAP) value ( r = 0.230, p < 0.001) and can be used to divide the severity of liver steatosis based on CAP value. Conclusions: This study demonstrated a easy-to-use model to detect high BMI, hyperlipidemia, and liver steatosis in people living with HIV without risk factors for BMI changing at baseline after 1 year of ART treatment.https://doi.org/10.1177/20406223221102750 |
spellingShingle | Zhe Qian Houji Wu Yihua Wu Wei Liao Tao Yu Xuwen Xu Jie Peng Shaohang Cai A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy Therapeutic Advances in Chronic Disease |
title | A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy |
title_full | A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy |
title_fullStr | A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy |
title_full_unstemmed | A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy |
title_short | A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy |
title_sort | model for predicting high bmi of people living with hiv after receiving antiretroviral therapy |
url | https://doi.org/10.1177/20406223221102750 |
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